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Containing the spread of mumps on college campuses
College campuses are vulnerable to infectious disease outbreaks, and there is an urgent need to develop better strategies to mitigate their size and duration, particularly as educational institutions around the world adapt to in-person instruction during the COVID-19 pandemic. Towards addressing thi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790351/ https://www.ncbi.nlm.nih.gov/pubmed/35116142 http://dx.doi.org/10.1098/rsos.210948 |
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author | Shah, Mirai Ferra, Gabrielle Fitzgerald, Susan Barreira, Paul J. Sabeti, Pardis C. Colubri, Andrés |
author_facet | Shah, Mirai Ferra, Gabrielle Fitzgerald, Susan Barreira, Paul J. Sabeti, Pardis C. Colubri, Andrés |
author_sort | Shah, Mirai |
collection | PubMed |
description | College campuses are vulnerable to infectious disease outbreaks, and there is an urgent need to develop better strategies to mitigate their size and duration, particularly as educational institutions around the world adapt to in-person instruction during the COVID-19 pandemic. Towards addressing this need, we applied a stochastic compartmental model to quantify the impact of university-level responses to contain a mumps outbreak at Harvard University in 2016. We used our model to determine which containment interventions were most effective and study alternative scenarios without and with earlier interventions. This model allows for stochastic variation in small populations, missing or unobserved case data and changes in disease transmission rates post-intervention. The results suggest that control measures implemented by the University's Health Services, including rapid isolation of suspected cases, were very effective at containing the outbreak. Without those measures, the outbreak could have been four times larger. More generally, we conclude that universities should apply (i) diagnostic protocols that address false negatives from molecular tests and (ii) strict quarantine policies to contain the spread of easily transmissible infectious diseases such as mumps among their students. This modelling approach could be applied to data from other outbreaks in college campuses and similar small population settings. |
format | Online Article Text |
id | pubmed-8790351 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-87903512022-02-02 Containing the spread of mumps on college campuses Shah, Mirai Ferra, Gabrielle Fitzgerald, Susan Barreira, Paul J. Sabeti, Pardis C. Colubri, Andrés R Soc Open Sci Computer Science and Artificial Intelligence College campuses are vulnerable to infectious disease outbreaks, and there is an urgent need to develop better strategies to mitigate their size and duration, particularly as educational institutions around the world adapt to in-person instruction during the COVID-19 pandemic. Towards addressing this need, we applied a stochastic compartmental model to quantify the impact of university-level responses to contain a mumps outbreak at Harvard University in 2016. We used our model to determine which containment interventions were most effective and study alternative scenarios without and with earlier interventions. This model allows for stochastic variation in small populations, missing or unobserved case data and changes in disease transmission rates post-intervention. The results suggest that control measures implemented by the University's Health Services, including rapid isolation of suspected cases, were very effective at containing the outbreak. Without those measures, the outbreak could have been four times larger. More generally, we conclude that universities should apply (i) diagnostic protocols that address false negatives from molecular tests and (ii) strict quarantine policies to contain the spread of easily transmissible infectious diseases such as mumps among their students. This modelling approach could be applied to data from other outbreaks in college campuses and similar small population settings. The Royal Society 2022-01-26 /pmc/articles/PMC8790351/ /pubmed/35116142 http://dx.doi.org/10.1098/rsos.210948 Text en © 2022 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Computer Science and Artificial Intelligence Shah, Mirai Ferra, Gabrielle Fitzgerald, Susan Barreira, Paul J. Sabeti, Pardis C. Colubri, Andrés Containing the spread of mumps on college campuses |
title | Containing the spread of mumps on college campuses |
title_full | Containing the spread of mumps on college campuses |
title_fullStr | Containing the spread of mumps on college campuses |
title_full_unstemmed | Containing the spread of mumps on college campuses |
title_short | Containing the spread of mumps on college campuses |
title_sort | containing the spread of mumps on college campuses |
topic | Computer Science and Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790351/ https://www.ncbi.nlm.nih.gov/pubmed/35116142 http://dx.doi.org/10.1098/rsos.210948 |
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